BEVACIZUMAB EFFECT ON TOPOTECAN PHARMACOKINETICS ...

BEVACIZUMAB EFFECT ON TOPOTECAN PHARMACOKINETICS IN A
MURINE ORTHOTOPIC RHABDOMYOSARCOMA XENOGRAFT MODEL
A Thesis
Presented for
The Graduate Studies Council
The University of Tennessee
Health Science Center
In Partial Fulfillment
Of the Requirements for the Degree
Master of Science
From The University of Tennessee
By
Zaifang Huang
December 2011

Copyright © 2011 by Zaifang Huang.
All rights reserved.
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ACKNOWLEDGEMENTS
I would like to thank my mentor, Dr. Clinton F. Stewart, for the opportunity to
learn from his vast knowledge and work in his laboratory. I also would like to express my
appreciation for his help, guidance, suggestion and encouragement throughout my study,
research and writing of this thesis. He is an incredible good mentor and career guider.
My sincere gratitude is also extended to the other members of my thesis
committee: Drs. John C. Panetta and Bernd Meibohm for serving on my committee and
their excellent suggestion, comments and guidance for this project. Especially, I want to
express my deepest gratitude to Dr. John C. Panetta for helping me with the population
modeling of this project. Without his help, I cannot accomplish this part of the work. I
also would like to thank Dr. Andrew M. Davidoff for providing the Rh30 cell line used in
this study.
In addition, I would like to thank to all the members and friends in the Stewart
laboratory. I would like to acknowledge my supervisor Dr. Stacy Throm and co-worker
Dr. Fan Wang for their patience, guidance and support during the project progress and
writing of the thesis. Thanks to the former post-docs Dr. Michael Tagen, Angel M.
Carcaboso and the former supervisor Laura Miller for their constant support and help.
I’m also grateful to co-workers and friends Dr. Feng Bai, Dr. Fan Zhang, Mohamed
Elmeliegy, Thandranese Owens, Dr. Steven Zatechka, Daniel Groepper, and Dr. Vamshi
Manda for their support and friendship throughout the project.
At last, I also would like to gratefully acknowledge the care and support of my
husband and parents, who always encouraged me on the way along.
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ABSTRACT
Increasing evidence suggests that inhibition of vascular endothelial growth factor
(VEGF) can transiently normalize tumor vasculature, thereby improving delivery of
systemic chemotherapy. Bevacizumab (BEV), an anti-VEGF antibody, has been shown
to transiently normalize tumor vasculature by increasing tumor vessel maturity,
decreasing tumor vessel permeability, and increasing tumor oxygenation in an Rh30
orthotopic rhabdomyosarcoma xenograft model. However, the effects of BEV on the
pharmacokinetics of TPT and the antitumor activity of TPT have not been evaluated. This
study aimed to investigate the effect of BEV on TPT systemic and tumoral
pharmacokinetics and to determine how these changes affect the efficacy of TPT in the
Rh30 mouse model.
Mice bearing Rh30 orthotopic xenografts were treated with BEV alone (5 mg/kg),
TPT alone (2 mg/kg) or a combination of the two administered intravenously with
different schedules. The pharmacokinetics of TPT, including TPT intratumoral
penetration, as well as the efficacy of the monotherapy and combination therapy were
evaluated. Population pharmacokinetic modeling and covariate analysis of TPT
pharmacokinetics were performed using the maximal likelihood expectation
maximization (MLEM) method in ADAPT 5 to predict the plasma and tumor
concentration-time profile, to estimate the pharmacokinetic parameters of individual
mouse and mice population, and to evaluate the effect of BEV on TPT systemic and
tumoral pharmacokinetics. Tumor penetration was assessed by the tumor-to-plasma ratio
of area under concentration-time curve (AUC). Tumor volume before and after the
treatment were measured to evaluate the antitumor activity of the treatment regimen, and
to assess the effect of BEV on the antitumor activity of TPT in Rh30 xenografts.
Covariate analysis showed a single dose of BEV was associated with the
increased systemic elimination rate and clearance of TPT. Furthermore, a single dose
BEV had a time-dependent effect on the tumor elimination rate of TPT. The elimination
rate of TPT from tumor compartment increased when it was given 1 day after a single
dose of BEV and gradually decreased to control level when TPT was given 3 days and 7
days after a single dose of BEV. Multiple doses of BEV had no effect on TPT
pharmacokinetics. TPT penetration was not altered after administering multiple doses of
BEV, but a single dose of BEV produced a trend in changes of TPT penetration. Tumor
efficacy was not dependent on the schedule of BEV and TPT. TPT significantly enhanced
the antitumor activity of combination therapy while pre-treatment of BEV did not alter
the antitumor activity of TPT. Tumor efficacy in MDBT groups was mainly due to the
multiple doses of BEV and the antitumor activity of TPT was diminished.
The present work provides crucial insights into the effect of coadministration of
BEV on the pharmacokinetic changes and antitumor activity of TPT. The increased TPT
systemic elimination and clearance after single dose of BEV treatment may be due to the
altered renal clearance by VEGF. The increased TPT elimination from tumor tissue after
1 day pre-treatment of BEV may be caused by a normalization of tumor vasculature. The
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overall effect of BEV on TPT pharmacokinetics as well as TPT penetration is determined
by the net balance of the pharmacologic changes of tumor microenvironment by BEV.
And the antitumor activity of combination is determined by the balance between
angiogenesis inhibition-induced tumor cell starvation and the tumor cytotoxicity due to
the exposure to cytotoxic drugs. This study highlights the complexity of pharmacokinetic
(PK) and pharmacodynamic (PD) interaction that may take place when antiangiogenic
agent and cytotoxic drug are combined and cautions that more consideration and
mechanistic investigation should be made before using a combination of anti-angiogenic
agents with cytotoxic drugs for cancer treatment.
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TABLE OF CONTENTS
CHAPTER 1. INTRODUCTION .....................................................................................1
1.1 Drug Penetration in Solid Tumors .......................................................................1
1.1.1 Features of tumor microenvironment ...............................................................1
1.1.2 Determinants for drug penetration in solid tumors ...........................................2
1.1.3 Strategies to improve drug penetration in solid tumors ....................................4
1.2 Angiogenesis and Anti-angiogenic Therapy ........................................................5
1.2.1 Angiogenesis in solid tumors ...........................................................................5
1.2.2 Role of vascular endothelial growth factor in tumor growth and
angiogenesis .....................................................................................................6
1.2.3 Anti-angiogenesis therapy and tumor vasculature normalization ....................6
1.2.4 BEV in preclinical studies ................................................................................7
1.2.5 BEV in patients .................................................................................................7
1.3 Rh30 Rhabdomyosarcoma as a Tumor Model ....................................................9
1.3.1 Rhabdomyosarcoma .........................................................................................9
1.3.2 Characteristics of Rh30 cell line .....................................................................10
1.4 Methods to Evaluate Drug Penetration in Solid Tumors ...................................11
1.4.1 Homogenization and quantitative imaging .....................................................11
1.4.2 Microdialysis ..................................................................................................12
1.5 The Effects of Anti-angiogenic Agents on the Pharmacokinetics of
Cytotoxic Drugs ................................................................................................13
1.5.1 The effects of anti-angiogenic agents on cytotoxic drugs disposition in
solid tumors ....................................................................................................13
1.5.2 The effects of BEV on cytotoxic drugs disposition in solid tumors ...............16
1.6 Pharmacokinetic Models of TPT in Preclinical Studies ....................................17
1.7 Summary ............................................................................................................18
1.8 Specific Aims .....................................................................................................19
CHAPTER 2. THE EFFECT OF BEVACIZUMAB ON THE
PHARMACOKINETICS OF TOPOTECAN IN A RH30
RHABDOMYOSARCOMA XENOGRAFT .................................................................20
2.1 Introduction ........................................................................................................20
2.2 Materials and Methods .......................................................................................21
2.2.1 Materials and chemicals .................................................................................21
2.2.1 Cell culture .....................................................................................................21
2.2.3 Animals ...........................................................................................................21
2.2.4 Tumor model and treatment ...........................................................................22
2.2.5 In vivo tumor microdialysis ............................................................................23
2.2.6 High-performance liquid chromatography analysis for PK studies ...............27
2.2.7 Pharmacokinetic model evaluation .................................................................27
2.2.8 Population pharmacokinetic analysis .............................................................29
2.2.9 Covariate analysis ...........................................................................................29
2.2.10 Statistical analyses ..........................................................................................30
2.3 Results ................................................................................................................30
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2.3.1 The effect of BEV on the pharmacokinetics of TPT ......................................30
2.3.2 The antitumor activity of the combination therapy ........................................40
CHAPTER 3. DISCUSSION AND CONCLUSIONS ..................................................43
LIST OF REFERENCES ................................................................................................47
VITA..................................................................................................................................59
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LIST OF TABLES
Table 1.
Table 2.
TPT penetration study design after a single dose of BEV treatment
(SDBT) .........................................................................................................24
TPT penetration study design after multiple doses of BEV treatment
(MDBT)........................................................................................................24
Table 3. TPT penetration after SDBT in mice bearing Rh30 RMS xenograft ............33
Table 4. TPT penetration after MDBT in mice bearing Rh30 RMS xenograft ..........35
Table 5. Population PK parameters of TPT estimated after SDBT ............................37
Table 6. Population PK parameters of TPT estimated after MDBT ...........................38
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LIST OF FIGURES
Figure 1. TPT efficacy study design after SDBT .........................................................25
Figure 2. TPT penetration plus efficacy study design after MDBT .............................26
Figure 3. A pharmacokinetic model for TPT ...............................................................28
Figure 4. The modified multi-compartmental PK model for TPT ...............................28
Figure 5.
Figure 6.
Figure 7.
Figure 8.
Representative plasma and tumor disposition of TPT with/without
SDBT in mice bearing Rh30 RMS xenograft ..............................................31
Representative plasma and tumor disposition of TPT with/without
MDBT in mice bearing Rh30 RMS xenograft .............................................32
The effect of BEV on the intratumoral exposure, plasma exposure and
intratumoral penetration of TPT after SDBT in mice bearing orthotopic
Rh30 RMS xenograft ...................................................................................34
The effect of BEV on the intratumoral exposure, plasma exposure and
intratumoral penetration of TPT after MDBT in mice bearing orthotopic
Rh30 RMS xenograft ...................................................................................36
Figure 9. The effect of treatment regimen on Ke and Kte ...........................................39
Figure 10.
Figure 11.
The effect of different schedule of SDBT combined with TPT on the
growth of orthotopic Rh30 tumors. ..............................................................41
The effect of different schedule of MDBT combined with TPT on the
growth of orthotopic Rh30 tumors. ..............................................................42
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LIST OF ABBREVIATIONS
ABC
ATP-binding cassette
ADA
Anti-drug antibodies
ARMS
Alveolar rhabdomyosarcoma
AUC
Area under concentration-time
AUCt
Area under concentration-time in tumor
AUCp
Area under concentration-time in plasma
BCRP
Breast cancer resistance protein
BEV
Bevacizumab
bFGF
Basic fibroblast growth factor
COG
Children’s oncology group
CGH
Comparative genomic hybridization
CPT-11
Irinotecan
CSF
Cerebrospinal fluid
CYP
Cytochrome p450
ECF
Extracellular fluid
ECM
Extracellular matrix
ERMS
Embryonal rhabdomyosarcoma
HPLC
High-performance liquid chromatography
IFP
Interstitial fluid pressure
IIV
Inter-individual variability
IRS
Intergroup rhabdomyosarcoma study group
IC
Intracerebral
IP
Intraperitoneally
IV
Intravenously
MDBT
Multiple doses of bevacizumab treatment
MLEM
Maximal likelihood expectation maximization
MMPs
Matrix metalloproteinases
MMP-2
Matrix metalloproteinase-2
MT1-MMP Membrane type 1 metalloproteinase
MVD
Microvessel density
NMR
Nuclear magnetic resonance
PBS
Phosphate buffered saline
PD
Pharmacodynamic
PDGF
Platelet-derived growth factor
PET
Positron emission tomography
PK
Pharmacokinetics
PTX
Paclitaxel
P-gp P-glycoprotein 1
QAR
Quantitative autoradiography
RD
Embryonal rhabdomyosarcoma cell line
RH30
Alveolar rhabdomyosarcoma cell line
RMS
Rhabdomyosarcoma
SD
Standard deviation
x

SDBT
Single dose of bevacizumab treatment
SC
Subcutaneous
TIMP-2 TIMP metallopeptidase inhibitor 2
TMZ
Temozolomide
TNP-470
O-(N-chloroacetyl-carbamoyl)-fumagillol
TPT
Topotecan
VEGF
Vascular endothelial growth factor
VEGFR
Vascular endothelial growth factor receptor
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CHAPTER 1.
INTRODUCTION
1.1 Drug Penetration in Solid Tumors
1.1.1 Features of tumor microenvironment
Solid tumors are structurally heterogeneous and complex. They are composed of
tumor cells and stromal cells such as endothelial cells, peri-vascular cells, fibroblasts and
myofibroblasts that are embedded in the extracellular matrix and nourished by the
vascular network [1]. Solid tumors have a unique microenvironment with several
characteristics that distinguish them from the corresponding normal tissue. Abnormal
solid tumor microenvironments are thought to be created by the interaction between the
tumor vasculature and the cells within the tumor [2]. The three major recognized
microenvironmental hallmarks of solid tumors are the abnormal vasculature, the
compacted extra-vascular compartment, and the unfavorable metabolic environment [3].
The first hallmark of solid tumors─the abnormal vasculature─is composed of
aberrant tumor angiogenesis, tortuous vascular architecture, heterogeneous vascular
permeability, and irregular blood flow [4-6]. Angiogenesis is the physiological process of
new capillaries generated from pre-existing blood vessels [7]. In normal tissue,
angiogenesis is controlled by a precise balance between pro- and anti-angiogenic factors
[8]. Blood vasculature in normal tissue consists of arterioles, capillaries and venules with
distinct features and is characterized by dichotomous branching [2]. However, in
pathological situations such as cancer, tumor cells can tilt the balance toward stimulatory
angiogenic factors to drive vascular growth in order to grow and metastasize to other
organs [9]. As a result, the tumor vasculature turns out immature and tenuous in nature.
Furthermore, tumor vessels share all features of three types of vessels─arterioles,
capillaries, and venules [2]. Thus tumor vasculature is marked by excessive branching
loops and arteriolar-venous shunts [10]. In addition, the walls of tumor vessels are
heterogeneous, with aberrant basement membranes, peri-vascular smooth muscle or
pericytes in different regions [11]. Also, tumor cells can incorporate into vessel walls
[12]. Thus tumor vessels are dilated, tortuous, disorganized, and have high permeability.
However, although the overall permeability is higher in tumor vessels compared to
normal blood vessels, some regions of tumor vessel walls can be normal or even thicker
than normal blood vessel walls and have less permeability [13, 14]. Moreover, blood flow
is controlled by arterio-venous pressure and vasculature geometric resistance [1]. In solid
tumors, decreased arterio-venous pressure, increased vasculature geometric resistance,
and the compression of blood vessels by tumor cells reduces the overall blood flow and
impair blood supply to the tumor cells [15-17]. In addition, the abnormality of vascular
architecture, blood vessel wall and blood flow can vary with location, with time, and
even in the same tumor region [18].
The second hallmark of solid tumors─the compacted extra-vascular
compartment─ is mainly displayed by the dysfunctional lymphatic system, interstitial
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hypertension and the pathologic extracellular matrix [19-21]. The major role of lymphatic
vessels is to drain the interstitial fluid from peripheral tissue to blood vessels and to
maintain the interstitial fluid balance in the tissue [19]. The rapid proliferation of tumor
cells compresses blood vessels and lymphatic vessels [17]. Accordingly, the lymphatic
system inside the solid tumors becomes dysfunctional and the blood vessels become
structurally and functionally abnormal [4-6, 11, 14-18]. However, there are functional
lymphatic vessels in the margin of the solid tumors or in the peri-tumor tissues [1]. Thus,
the interstitial fluid is confined within solid tumors, and interstitial fluid pressure is
uniformly high throughout the core of a solid tumor, while dropping dramatically in the
tumor margin [22, 23]. The extracellular matrix (ECM) consists of basement membrane
and interstitial stroma. The basement membrane mainly contains collagen IV, laminin
and proteoglycans, while the interstitial stroma mainly contains fibrillar collagens,
fibronectin, hyaluronic acid, and fibril-associated proteoglycans [24]. In solid tumors, the
components in ECM are dynamically changed and large amount of these components are
overexpressed, attributable in part to the extensive synthesis of ECM [25-27].
Furthermore, the fast growth of tumor cells within a limited space also squeezes or
compresses the ECM into a compacted pattern [28, 29].
The third hallmark of solid tumors─the unfavorable solid tumor metabolic
environment─is the low levels of oxygen and acidic pH [30-32]. Due to an imbalance
between tumor cell proliferation and vasculature development, multiple regions of cells
in solid tumors are distant, such as 180 µm away from blood vessels, so that oxygen
cannot be transported and diffused to those regions [33, 34]. This chronic effect of
hypoxia results in multiple necrotic regions in solid tumors. Even though the tumor cells
are close to the blood vessels, they can also undergo acute hypoxia due to the intermittent
and irregular blood flow [35]. The low extracellular pH is due to increased production
and reduced removal of H + ions [1]. The main sources of increased H + ions production
are from anaerobic glycolysis under the hypoxia condition and from CO 2 and H 2 O by
carbonic anhydrase [36]. The reduced removal of H + ions is caused by abnormal
microcirculation.
In conclusion, the microenvironment in solid tumors displays an aberrant vascular
compartment, a compacted extra-vascular compartment, and unfavorable metabolic
environment.
1.1.2 Determinants for drug penetration in solid tumors
After reaching the systemic circulation, therapeutic drugs quickly diffuse through
the vasculature and distribute within the solid tumors. Drug penetration in solid tumors
depends on several factors, including the physicochemical properties of the drug,
formulation, and the delivery system of the drug as well as the neoplastic tissue
microenvironment. For a formulated drug product, there are three major determinants or
barriers in solid tumors that inhibit drug penetration from systemic blood circulation to
the therapeutic target cells: the aberrant blood vessel architecture, the heterogeneous
vessels’ wall, and the compacted extracellular matrix [37].
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The therapeutic agents depend on blood circulation to reach the targeted tissue, so
the pathologic vasculature is the first determinant for drug penetration in solid tumors
[38]. The distribution of the drug in tumor is governed by the blood vessel morphology
and the blood flow rate in the tumor [39]. As discussed above, the number, length,
diameter and geometric arrangement of blood vessels are irregular and the blood flow
rate is fluctuated in solid tumors. Consequently, some regions are well perfused while
other regions are totally unperfused within the same tumor [40]. Accordingly, the drug
can accumulate in one region but not access another region at all. Furthermore, cessation
of blood flow will reduce net tumor cell ‘exposure’ to the therapeutic agents in blood
circulation and even intermittent decreases in blood flow will impact on the net
distribution (AUC) of systemically administered agents [41].
Additionally, the blood vessel wall in solid tumors also affects the ability of
therapeutic drugs to diffuse universally to extra-vascular space [42]. The blood vessel
wall is heterogeneous and hyperpermeable with thick or thin basement membrane, less or
more pericytes and maximum diameter of the irregular pores [12]. The leaky wall of the
blood vessel is likely to yield higher drug uptake; however, interstitial hypertension
prevents the convective transport of drug between intra-vascular and extra-vascular
spaces [43]. Since the interstitial pressure is high throughout the core of the solid tumor
but drops dramatically in the tumor margin, the drug tends to distribute in the tumor
peripheral region rather than the center of it [23], resulting less drug penetration in the
core of solid tumors.
Lastly, the condensed interstitium and unfavorable metabolic environment
dramatically hinder the drugs from accessing tumor cells [25]. Tumor cells are highly
packed, and the extracellular matrix is compressed by tumor cells, both of which reduce
drug penetration in solid tumors [28]. Drug penetration and the efficacy of anticancer
drugs are considerably decreased in tightly packed cells compared to loosely packed cells
[44]. Similarly, the well organized and extensively interconnected collagen network in
the extracellular matrix severely affects drug movement in the interstitium [25]. The
harsh microenvironment with hypoxia and acidic pH may also impair drug penetration in
solid tumors. For example, too much hypoxia leads the hypoxia-activated prodrugs (such
as tirapazamine, AQ4N, and PR-104) to extensive metabolism, leaving no drug
remaining to penetrate to the targeting sites [45]. And weak basic drugs (such as
doxorubicin and mitoxantrone) or weak acidic drugs (such as methotrexate) have shown
slower drug penetration in acidic solid tissues [46, 47].
Thus, there are multiple determinants in solid tumors that hinder a drug from
effectively penetrating to the tumor cells and exerting its cytotoxic action. In order to
overcome this obstacle, many investigators have developed useful strategies to improve
drug penetration in solid tumors.
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1.1.3 Strategies to improve drug penetration in solid tumors
The strategies to improve drug penetration in solid tumors mainly fall into two
categories: 1. Normalize the tumor microenvironment including tumor vasculature and
extracellular matrix (ECM). 2. Develop more effective delivery methods for drug
penetration or modifying drug property for deeper penetration.
The first strategy that investigators tried is to ameliorate the microenvironment of
solid tumors for drug penetration, normalizing the tumor vasculature and tumor matrix
[42]. Overexpression of proangiogenic molecules such as vascular endothelial growth
factor (VEGF), basic fibroblast growth factor (bFGF) and platelet-derived growth factor
(PDGF) may be the major cause of the structurally and functionally abnormal vasculature
in solid tumors [14]. Blocking these pro-angiogenic factors leads to increased apoptosis
of endothelial cells and therefore elimination of immature blood vessels, creating tumor
vessels with closer resemblance to normal vessels in structure and function [14]. The
features of tumor vasculature normalization may include the reduction of microvessel
density, interstitial fluid pressure (IFP), and hypoxia as well as the increase of blood flow
and perfusion rate [48]. Numerous studies have shown that normalization of tumor
vasculature via anti-angiogenesis therapy improves cytotoxic drug penetration in solid
tumors. Increased paclitaxel (PTX) concentration in two solid tumor tissues after
combining with BEV, an anti-VEGF monoclonal antibody, has recently been observed
accompanying the downregulation of vascular permeability [49]. In a MX-1 human
breast cancer xenograft, the intratumoral PTX concentration in mice treated with a single
dose of PTX 30 mg/kg plus a single dose of BEV 5.0 mg/kg was significantly higher than
in the tumor treated with PTX 30 mg/kg alone (5.75±0.31 µg/g vs. 4.00±0.85 µg/g). And
the PTX concentration in tumor treated with PTX 30 mg/kg plus BEV 5.0 mg/kg was
equivalent to that in the tumor treated with either 60 or 100 mg/kg of PTX alone. An
increase in PTX concentration by BEV was also observed in an A549 human lung cancer
xenograft model. In the same MX-1 model, vascular permeability in the tumor was
significantly decreased by treatment with BEV. DC101, a VEGF-receptor-2 antibody, has
been shown to normalize tumor vasculature and increase BSA penetration in several solid
tumors [50]. Combining sunitinib, an inhibitor of several tyrosine kinase receptors
(including vascular endothelial growth factor receptors, platelet-derived growth factor
receptors and stem cell factor receptor), with temozolomide significantly increases the
penetration of temozolomide in human glioma xenografts. This enhanced penetration is
associated with an improved “vascular normalization index” incorporating the
microvessel density (MVD) and protein expression of α-SMA and collagen IV [51].
Other than the normalization of vasculature, the normalization or degradation of ECM
also can improve the uptake and penetration of drugs. As discussed above, the well
organized collagen network slows the penetration rate of cytotoxic drugs. The addition of
collagenase induces a two-fold increase in tumor uptake and improves the distribution of
the monoclonal antibody TP-3 in a human osteosarcoma xenograft by degrading ECM
while decreasing IFP and microvascular pressure [52]. Furthermore, reducing the packing
density of tumor cells by chemotherapy itself can relieve the compacted ECM by killing
tumor cells, decompressing blood vessels and decreasing IFP, which results in increased
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drug penetration. Pre-treatment with 1 μM non-radiolabeled paclitaxel enhanced the
penetration rate of [ 3 H] paclitaxel in a human pharynx FaDu xenograft [53].
The second strategy that researchers have used is a targeting delivery system or
improved drug property to increase the drug distribution in solid tumors. The targeting
delivery system mainly uses two principles: passive targeting or active targeting [54].
Passive targeting involves enhancing the drug carrier permeability and retention in solid
tumors by designing the particle size too large to diffuse through normal blood vessels
but small enough to exit the abnormally large pores on the tumor vessel walls to
extra-vascular space. With more drugs in the extra-vascular space by the passive
targeting system, relatively more drug will diffuse into solid tumors and restrict it in the
tumor tissue due to lack of a functional lymphatic system [55]. The active targeting
strategy employs the specific tumor microenvironment by attaching ligands to the carrier
surface that can bind to tumor specific receptors and antigens through molecular
recognition. These receptors and antigens include the cancer cell surface antibodies [56],
folate receptor [57], transferrin receptors [58] and angiogenic vascular surface proteins
[59]. Another modification for deeper drug penetration is to use live bacterial vectors
such as Salmonella sp, Clostridium sp and Escherichia coli based on their
tumor-colonizing characteristics [60]
In summary, numerous strategies have been developed to increase cytotoxic drug
penetration in solid tumors. The normalization of tumor vasculature is one of the most
popular methods to enhance drug penetration.
1.2 Angiogenesis and Anti-angiogenic Therapy
1.2.1 Angiogenesis in solid tumors
Angiogenesis is the physiological process of new capillaries generation from
pre-existing blood vessels [7]. In normal tissue, angiogenesis is precisely regulated by
keeping a balance between pro-angiogenic factors, such as VEGF and PDGF, and
anti-angiogenic factors, such as thrombospondin-1 and angiostatin [61]. Regulated
angiogenesis provides organs and tissue sufficient nutrition and oxygen to grow and
recover from wound healing [62]. Under pathological conditions, the balance of
pro-angiogenic factors and anti-angiogenic factors is broken and leads to dysfunctional
and structurally abnormal vasculature. Unregulated angiogenesis plays a critical role in
solid tumor growth and metastasis [63]. As in normal tissue, a tumor beyond 0.5mm in
diameter relies on angiogenesis to supply nutrition and oxygen for survival and growth
[64]. Furthermore, the dilated and leaking intra-tumoral blood vessels allow the tumor
cells to enter the blood circulation and metastasize to distant organs [65]. In this context,
the anti-angiogenesis approach as a tumor treatment strategy has been investigated
extensively.
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1.2.2 Role of vascular endothelial growth factor in tumor growth and angiogenesis
Vascular endothelial growth factor-A (also termed VEGF) is a key angiogenic
mediator [65]. As early as 1996, the group at Genentech led by Dr. Napoleone Ferrara
showed that even loss of a single VEGF allele resulted in several impaired developmental
vasculature abnormities and was lethal in the mouse embryo between days 11 and 12
[66]. Furthermore, the overexpression of VEGF is frequently found in human solid
tumors [67, 68]. A elevated expression of VEGF is found to correlate to tumor
angiogenesis, progression and survival in patients [69].
There are multiple isoforms of VEGF, ranging from 121 to 206 amino acids, and
all the isoforms can bind to two receptors: VEGFR-1 and VEGFR-2 [70]. The major
activities of VEGF in endothelial cells are regulated by signaling via VEGFR-2 [71].
Blockage of VEGF/VEGFR pathways is sufficient to suppress vasculature in numerous
solid tumor models and inhibition of these pathways also results in tumor growth
suppression [72]. Among these VEGF/VEGFR inhibitors, BEV, a monoclonal antibody
specific for VEGF, is the most extensively studied candidate in preclinical and clinical
settings.
1.2.3 Anti-angiogenesis therapy and tumor vasculature normalization
In 1971, Dr. Folkman [73] proposed that the inhibition of angiogenesis might be
an effective strategy to treat human cancer. Thereafter, a large body of literature
discussed the investigation of angiogenesis inhibitors. Driven by this hypothesis, Dr.
Folkman’s lab developed the first anti-angiogenic agents in the early 1980s [74, 75], and
additional synthetic and endogenous angiogenesis inhibitors were discovered by
numerous labs [76-79]. In the mid-1990s, the angiogenesis inhibitors started to enter
clinical trials. In 2004, the first anti-angiogenic agent, bevacizumab (BEV), was approved
by the FDA for colorectal cancer [80]. Currently, over 2,000 clinical trials in USA are
testing drugs that have varying degrees of anti-angiogenic activity for different types of
cancers; over 300 of these clinical trials are in phase III.
After decades of effort, the tumor normalization concept emerged in 2005 from
Dr. Jain’s research [14]. The concept is: under a pathological condition, the imbalance of
the pro-angiogenic factors and anti-angiogenic factors persists. Restoring this imbalance
or making the imbalance favor the anti-angiogenic factors may lead to vascular
regression or a close to normal condition and ultimately lead to the prevention of tumor
growth and metastasis. Additionally, Dr. Jain proposed a vascular normalization window
when using proper dosing and scheduling of angiogenesis inhibitors. This concept was
widely accepted by the field and, indeed, numerous investigators identified this
normalization window. For instance, the recent study, in which mice bearing orthotopic
U87 xenografts were treated with BEV or interferon β, showed that the anti-angiogenic
agent treatment induced significant changes in tumor vascular physiology, improving
intra-tumoral oxygenation and enhancing the antitumor activity of ionizing radiation [81].
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However, the window for human U87 tumor model is transient and only lasts about 5
days.
1.2.4 BEV in preclinical studies
Numerous studies have been conducted to investigate the pharmacological effect
of BEV in solid tumor xenograft models. Investigators have mainly focused on tumor
growth inhibition via disruption of tumor vasculature and the inhibition of tumor
metastasis.
In general, studies of the anti-VEGF effect usually employed vascular changes
and tumor growth inhibition as primary end points and have showed that BEV
significantly decreased vessel density and tumor growth regardless of tumor types. Dr.
Finn et al. showed that administration of BEV 5 mg/kg intra-peritoneal twice a week
significantly decreased microvessel density, decreased human serum alpha-fetoprotein
and delayed tumor progression for treated mice compared to the controls in a human
hepatocellular orthotopic xenograft model [82]. Dr. Okada et al. administered BEV 2
mg/kg intra-peritoneal twice a week for 8 weeks and found that BEV significantly
inhibited tumor growth by 48% in volume at the end of the experiment [83]. Meanwhile,
the intratumoral microvessel density was significantly decreased in the BEV treatment
group compared to the control group and a positive correlation was found between tumor
volume and microvessel density.
VEGF plays a critical role in the tumor angiogenesis and angiogenesis is a feature
of growth and invasion in primary neoplasms and their metastases. Furthermore, BEV
has been shown to control metastatic colorectal carcinoma, metastatic breast carcinoma,
and metastatic non–small cell lung carcinoma [84-86]. However, there are also several
case reports about more cancer metastasis after BEV treatment [87, 88]. Thus some
investigators start to assess the anti-VEGF effect on tumor metastasis. Imaizumi et al.
used a peritoneal metastasis model to determine the effect of BEV on peritoneal
dissemination from gastric cancer and showed BEV had a significant effect on peritoneal
dissemination suppression [89]. More directly, Dr. Yang et al. examined the effect of
BEV on tumor cell survival, invasiveness in vitro and metastasis in vivo [90]. The results
showed that BEV decreased in vitro growth and invasion and further suppressed in vivo
hepatic metastasis of ocular melanoma cells.
Based on the promising tumor vasculature and growth inhibitory effects of BEV
in preclinical models, the application of BEV was moved forward to clinical trials.
1.2.5 BEV in patients
Although BEV showed a significant effect on tumor vasculature changes, tumor
growth, metastasis and survival rate in preclinical studies, BEV alone only provides
modest survival benefits in patients [91]. However, it showed that anti-VEGF treatment
7

enhanced the tumor response to conventional chemotherapy. Thus, currently the primary
use of BEV in clinical patients is in combination with conventional chemotherapy [92].
The precise mechanism of how BEV enhances the conventional regimens is
unclear, but at least four mechanisms have been proposed:
1. Enhancement effect of conventional cytotoxic drug penetration by tumor
vasculature normalization [14].
2. Synergic effect of BEV and cytotoxic drugs on tumor cells that express and
depend on VEGF for growth and survival [93].
3. The anti-angiogenic effect of cytotoxic drugs facilitates the VEGF depletion
by BEV [94].
4. The additive effect of BEV and cytotoxic drugs on both tumor cells and
endothelial cells [95].
The overall improved outcome due to BEV, combined with conventional
cytotoxic drugs, is the consequence of one or more of the mechanisms mentioned above
functioning together. Clinical studies have showed that the addition of BEV to
conventional chemotherapy provides significant survival benefits on cancer patients with
diverse solid tumor types such as breast cancer [96], colorectal cancer [80, 97, 98] and
non-small-cell lung cancer (NSCLC) [99-101]. Dr. Miller et al. compared the
progression-free survival (PFS) and overall survival (OS) for patients with metastatic
breast cancer receiving PTX alone and PTX plus BEV [96]. This phase III trial indicated
that PTX plus BEV significantly prolonged PFS as compared with PTX alone (median,
11.8 vs. 5.9 months; hazard ratio for progression, 0.60; p

1.3 Rh30 Rhabdomyosarcoma as a Tumor Model
1.3.1 Rhabdomyosarcoma
Rhabdomyosarcoma (RMS) arises from immature cells that are developed to form
striated skeletal muscle, but it can virtually arise at any site and in any tissue in the body
except bone [102]. Head and neck are the most common regions where RMS occurs
(approximately 40%); the genitourinary sites and the extremities are the next most
frequent regions where RMS arises (approximately 20% each); and the remaining 20%
RMS initiates from other sites, such as parameningeal sites and the retroperitoneum
[103].
The two most common pathologic types of RMS are embryonal and
alveolar[102]. Embryonal rhabdomyosarcoma (ERMS) is the most common RMS seen in
infants and young children, comprising of more than 60% of all RMS. The ERMS cells
[104] exhibit the normal developing muscle cells, such as stellate undifferentiated
mesenchymal cells, elongated myoblasts, multinucleated myotubes, and fully
differentiated myofibers. ERMS has a better prognostic outcome [105-107] than other
subtypes and tends to occur in the genitourinary tract, head and neck, and abdomen.
About 20% of all rhabdomyosarcoma are of the alveolar histology (ARMS) [108], in
which cells look like the mature muscle cells in a 10-week-old fetus. ARMS grows much
faster than ERMS, needs more intensive treatment, has a higher relapse incidence and
worse prognostic outcome[109].
RMS occurs more frequently in children and adolescents (

non-favorable sites [109]. So developing new agents or new strategies to increase the
current agent efficacy is urgently needed for the treatment of RMS, especially ARMS.
1.3.2 Characteristics of Rh30 cell line
The Rh30 cell line we chose for the tumor xenograft model is highly complex in
genetic profile and overexpression of VEGF, VEGFR and MMP-2, which is associated
with more aggressive invasion behavior and is characterized as an ARMS subtype.
ARMS is genetically characterized by reciprocal translocations that generate the
fusion gene PAX3-FOXO1A (PF) or PAX7-FOXO1A. The Rh30 cell line is characterized
as ARMS cell line and positive for PAX3-FOXO1A fusion gene. By applying any of
several techniques such as spectral karyotyping, fluorescence in situ hybridization,
comparative genomic hybridization (CGH), and microarray CGH, Rodriguez-Perales et
al. [113] found Rh30 had a wide range of chromosome numbers, more than 50
chromosome rearrangements, amplification of the hybrid gene, 24 DNA changes and 21
gene copy changes. p53 is also mutated in the Rh30 cell line with a codon 280 A to T
transversion (arginine to serine) [114].
VEGF is overexpressed in the Rh30 cell line, which provides a rationale for our
selection of it for anti-VEGF therapy. Moreover, the overexpression of MMP-2 renders
Rh30 more invasive than ERMS cell lines [115]. Onisto et al. studied the MMP-2,
MT1-MMP, TIMP-2, VEGF and VEGF receptors in several ARMS, ERMS and
undifferentiated cell lines and tried to correlate the metastatic potential with the matrix
metalloproteinases (MMPs) and angiogenesis-related factors. The results showed that
Rh30 had increased expression levels of both VEGF 165 and VEGF 121 isoforms as well as
VEGFR-1 at mRNA and protein. Also the elevated expression of MMP-2 at mRNA and
protein levels correlated with the invasive behavior in vitro.
Comparing the ERMS cell line RD, Rh30 cell line is more sensitive to
camptothecin and its derivative TPT [116], and the effective schedules of exposure of
Rh30 xenografts to TPT have been identified [117]. By high-throughput screening, Zeng
et al. showed that camptothecin and TPT inhibited cell proliferation and induced cell
apoptosis more effectively in Rh30 than in RD (ERMS) cells. Ectopic expression of the
fusion protein PF in RD cells significantly increased their sensitivity to camptothecin and
TPT, whereas siRNA knockdown of PF decreased the sensitivity of Rh30 cells to
camptothecin and TPT [116]. Furthermore, Dr. Stewart and his collaborators showed that
TPT was highly schedule-dependent in Rh30 cells and that only daily exposure of TPT
achieved complete regressions of Rh30 xenografts [117]. The dose and schedule for
complete regression in Rh30 xenografts was to give TPT daily 0.6mg/kg for 2 weeks,
repeated every 21 days for three cycles. However, preclinical and clinical studies showed
that rhabdomyosarcoma is resistant to TPT [118, 119]. To overcome the drug resistant
and increase its efficacy, one of the approaches is to increase its intratumoral
concentration. Thus, we used Rh30 orthotopic rhabdomyosarcoma xenograft as a tumor
10

model to investigate the effect of schedule-dependent anti-VEGF treatment on TPT
disposition and tumoral penetration in an orthotopic model of RMS in mice.
1.4 Methods to Evaluate Drug Penetration in Solid Tumors
1.4.1 Homogenization and quantitative imaging
Several techniques [120] have been used to quantitate drug concentration in solid
tumors, including collecting tumor homogenate, using noninvasive quantitative imaging
and sampling by microdialysis, which will be discussed in detail in the following section.
The use of tumor homogenates is a widely used technique to determine drug
concentration in normal and tumoral tissues. This method was used frequently in early
drug pharmacokinetic studies [121-123] and currently is still commonly employed in this
field [124, 125]. Although this approach has multiple advantages (such as easy to
implement, achieving results quickly, and getting large amount of samples for PK/PD
studies simultaneously), it has several disadvantages as well. The concentration obtained
by this sampling method is the total drug concentration, including protein bound and
unbound drugs that are present in tumor vascular, the interstitial space, and intratumoral
compartments. This mixed concentration complicates the interpretation of the results
since the unbound free drug is the pharmacologically active drug. Additionally, the total
drug from these compartments also limits insight into underlying drug distribution and
transport mechanisms. Another drawback of this approach is that only one sample can be
obtained from each animal. In order to get adequate information for the drug disposition
in the tumor, one has to sacrifice multiple animals to get adequate data to interpret drug
disposition or penetration, which requires considerable animal resources. Furthermore,
this approach also leads to wide inter-animal variability, which can complicate the
interpretation of the data.
An alternative way to quantify drug concentration in the tumor tissue is to use
quantitative imaging such as positron emission tomography (PET) [126, 127],
quantitative autoradiography (QAR) [128], and nuclear magnetic resonance (NMR) [129,
130]. PET scanning combines computerized tomography (CT) and radioisotope imaging.
By injecting radiolabeled drug, it is possible to map drug distribution in the body or the
target tissue-tumor. When combining pharmacokinetic tools, it is also possible to
determine the kinetic changes of the radiolabeled drug and various physiological
parameters [131]. While PET has low spatial resolution, QAR can measure radiolabeled
drug concentration in small regions of the target tissue. However, the main limitation of
these two techniques is the instability of isotope. Therefore, synthesis of the radioisotope
must take place immediately before the in vivo experiment, and correction for the decay
of the isotope is essential to obtain reliable results. Furthermore, both of these two
techniques cannot distinguish between parent drugs and metabolites, nor between
protein-bound drugs and free drugs [120]. While NMR is able to differentiate between
parent drug and its metabolites as well as protein bound and unbound drugs, it has very
11

low sensitivity. Additionally, it requires a long time to obtain signals while keeping small
animal in a fixed position, which adversely affects the time resolution. Furthermore, the
spatial resolution of NMR is also limited [132]. Nevertheless, noninvasive imaging
techniques may reduce inter-individual variability since multiple time samples can be
obtained from each animal [120].
1.4.2 Microdialysis
Currently, the microdialysis technique has acquired more attention than these
techniques mentioned above and is widely accepted by many studying drug penetration to
tissues and tumors. Microdialysis sampling has gained popularity [133] in preclinical and
clinical pharmacokinetic studies since it was introduced by Delgado [134] in 1972 for its
application in preclinical pharmacokinetic studies. This technique involves the insertion
of a semi-permeable probe affixed to the inlet and outlet tubing. The probe virtually can
be placed in any tissue such as brain, blood, liver, skin and solid tumors [135-139]. It is
perfused by a solution that closely matched to the medium of the surrounding tissue, and
the analyte is collected by the diffusion over the probe membrane and down its
concentration gradient from the target tissue into the perfusate, which runs continuously
out to the outlet tubing after drug administration.
Microdialysis has a number of advantages for in vivo sampling of drugs. The
perfusion solution is isotonically matched to tissue extracellular fluid, so there is no fluid
loss for the continuous sampling and minimal interruption to the integrity of PK
determinants. Secondly, collecting serial samples from one animal not only reduces the
number of animals needed but also minimizes the inter-individual variability of the data
[120]. More importantly, the microdialysate contains only protein unbound free drug,
which may facilitate a clear pharmacological interpretation and readily support
physiologically based PK/PD models [140, 141]. Additionally, microdialysis is
applicable to measure parent drug and its metabolites simultaneously since radiolabeled
drugs are unnecessary [142, 143]. Furthermore, microdialysis only samples molecules
with smaller molecular weight than the probe molecular weight cut-off, such as 5 or 20
kDa. So it automatically excludes a lot of drug degradation enzymes and cleans up the
samples, thus avoiding the ex vivo enzymatic degradation and pre-analysis processing.
The main limitation of microdialysis is the probe calibration or in vivo recovery
assessment to get the true concentration in the surrounding tissue that contradicts the
advantage of the reduction of animal subjects and inter-individual variability. Secondly,
since only a very small volume (15-50 microliters) of sample can be retrieved from each
time point, it requires more sensitive analytical methods to quantify the drug
concentration in the samples. Third, the invasiveness of the probe insertion also raises
concerns of the interruption of the physiological system. However, investigators [144]
showed that if the animals are given adequate time (e.g., 24 hours for intracranial
microdialysis) to recover, the tissue damage can be managed. Despite these limitations,
the ability to continuously sample unbound and presumably active drugs in the specific
12

tissue region renders microdialysis a powerful and appealing technology that is applied
more and more in drug delivery and pharmacokinetic studies.
1.5 The Effects of Anti-angiogenic Agents on the Pharmacokinetics of Cytotoxic
Drugs
1.5.1 The effects of anti-angiogenic agents on cytotoxic drugs disposition in solid
tumors
The effects of anti-angiogenic agents on cytotoxic drug disposition in solid
tumors are paradoxical: Some investigators found that anti-angiogenic agents decrease
the penetration of cytotoxic drugs into solid tumors; some indicated that anti-angiogenic
agents increase the uptake of cytotoxic drugs into solid tumors, while others
demonstrated that the delivery of cytotoxic drugs into solid tumors does not change after
the administration of anti-angiogenic agents.
Several studies showed pre-treatment with angiogenesis inhibitors decreased
temozolomide (TMZ) concentration or exposure in rat glioma xenografts. In 1996, Dr.
Gallo et al. examined the TMZ interstitial fluid concentration by using the microdialysis
technique in a subcutaneous (SC) rat C6 glioma xenograft model after multiple doses of
the angiogenesis inhibitor O-(N-chloroacetyl-carbamoyl)-fumagillol(TNP-470) [145].
TNP-470 (30 mg/kg) was given SC on days 6, 8, 10, 12, and 14 following tumor
implantation. On day 15, control (no TNP-470) and treated rats received 40 mg/kg of
TMZ intra-arterially. Plasma and interstitial fluid samples were collected for 8 h and
non-compartmental methods were used for pharmacokinetic modeling. The results of this
study indicated that the mean TMZ area under the interstitial fluid concentration-time
curve was reduced by 25% in the TNP-470-treated group compared to the control. In a
subsequent study, the same group determined the tumor distribution of TMZ in SC and
intracerebral (IC) rat glioma models with the overexpression of VEGF (V+) after
anti-angiogenic agent TNP-470 [146] administration. TNP-470 (30 mg/kg) was
administered to the animals SC every other day for total 5 doses (SC tumor model) or 4
to 6 doses (IC model) which is coincided with the presentation of the central nervous
system symptom [146]. The day after the last dose of TNP-470, TMZ was administrated
intra-arterially to achieve steady-state plasma concentration of 40 μg/ml. The steady-state
concentration of TMZ in tumor ECF and plasma as well as the concentration of TMZ
metabolite 5-(3-methyltriazen-1-yl) imidazole-4-carboximide (MTIC) in tumor ECF were
determined and microvessel density (MVD) was quantitated using an anti-CD31 method.
In both the V+ SC and V+ IC models, significant reductions in TMZ tumor
concentrations and tumor-to-plasma concentration ratios compared with control after
TNP-470 treatment were observed, being reduced an average of 25% and 50% in the SC
and IC tumors, respectively. MTIC concentrations in V+ SC tumors also were reduced by
50% after TNP-470 administration. Consistent with the reduction of TMZ and MTIC
concentration in tumor ECF, MVD was reduced by TNP-470 compared with vehicle
control in the V+ SC and V+ IC tumors. Additionally, Gallo et al. also determined the
13

tumor distribution of TMZ in V+ SC and V+ IC rat glioma models after another
anti-angiogenic agent 3-[(2,4-dimethylpyrrol-5-yl)methylidenyl] indolin-2-one (SU5416)
administration [147]. SU5416 (25 mg/kg) or vehicle control was administrated
intraperitoneally (IP) daily for a total of nine doses. Two days after the last dose of
SU5416 or vehicle control, TMZ was administration as a steady-state infusion regimen to
achieve plasma concentrations of 20 μg/ml. In V+ SC tumors, a 24% reduction in
steady-state plasma TMZ concentration as well as a 21% reduction in tumor-to-plasma
concentration ratio was documented compared with controls. This reduction was also
accompanied by a 20 to 35% reduction in MVD. In contrast with TNP-470 study, In a V+
IC tumor xenograft model, steady-state plasma TMZ concentration and tumor-to-plasma
ratio were significantly increased by 2-fold after SU4516 treatment compared to controls.
The authors discussed that the differential effects of SU4516 in tumor distribution of
TMZ in V+ SC and V+ IC tumor models may be attributed to the microdialysis sampling
site, peripheral versus central, and the dimethyl sulfoxide administration vehicle.
In contrast to the reduction of cytotoxic drug penetration and concentration in
tumor tissue after antiangiogenesis therapy, there were publications showed that
antiangiogenic agents can improve the drug delivery to tumor site in addition to the
observation in V+ IC rate model discussed in above paragraph. Gallo and colleagues
published two papers [51, 148] that demonstrated that a lower dose of sunitinib
significantly increased TMZ tumor distribution in two mice glioma xenografts when
compared to a higher dose or control group. In mice bearing SF188V+ human glioma
xenografts, vehicle, sunitinib (10 mg/kg) or sunitinib (40 mg/kg) was given everyday
orally up to 14 days [51]. One day after the last dose of vehicle or sunitinib, TMZ was
administrated as a single oral dose at 20 mg/kg. Both sunitinib dosage 10 mg/kg and 40
mg/kg increased temozolomide tumor distribution by using tumor-to-plasma AUC ratio
compared to control group. However, only 10 mg/kg group reached statistical
significance (p

efficacy study, CPT-11 was equally effective with or without pretreatment with A4.6.1.
The authors concluded that tumor vascular function and tumor uptake of anticancer drugs
improved with VEGF-blocking therapy. Finally, as discussed in the second paragraph of
section 1.1.3, increased PTX concentration in two solid tumor tissues after a single dose
of BEV (5 mg/kg) has recently been observed accompanying the downregulation of
vascular permeability [49]. Consistent with the increased intratumoral PTX
concentration, the antitumor activity of BEV at 5 mg/kg in combination with PTX at 20
or 30 mg/kg was significantly higher than that of either agent alone. The authors
concluded that the synergistic antitumor activity of PTX and BEV in combination may be
a result of the increase in PTX concentration in tumor resulting from the downregulation
of vascular permeability when co-administered with BEV.
The underlying reasons for this paradoxical phenomenon have been discussed by
numerous investigators. As mentioned in section 1.1, the poorly organized and irregular
tumor vasculature leads to reduced blood flow, heterogeneous vessel wall and interstitial
hypertension and results in inefficient delivery of cytotoxic drugs into tumors. The uptake
of cytotoxic drugs [91] in tumors is primarily determined by the total number of
functional blood vessels inside the tumor and the transport efficiency of each individual
vessel. The treatment of anti-angiogenic agents dynamically affects the tumor vasculature
and the consequent cytotoxic drugs transport into solid tumors. Besides, the optimal
dosing and scheduling of angiogenesis inhibitors when combining with cytotoxic drugs
are critical for the effect of angiogenesis inhibitors on cytotoxic drug penetration and
efficacy, as extensively suppression of tumor vessels may ultimately reduce the cytotoxic
drug penetration and efficacy. Indeed, improved clinical responses were observed when
conventional chemotherapy was combined with low dose BEV as compared to high dose
BEV [98]. Improved intratumoral cytotoxic drug concentration and penetration were also
observed when given low dose of sunitinib as compared to high dose sunitinib [51, 148].
In addition, chronic treatment with antiangiogenesis therapy eventually reduces tumor
blood perfusion and increases tumor hypoxia in experimental animal studies [150, 151],
indicating that uninterrupted treatment with the anti-angiogenic drug, although perhaps
maximally effective as a monotherapy, may not be optimal for tumor vascular
normalization-enhanced combination chemotherapy. Furthermore, as Jain [14] proposed,
either less effect or over pruning of tumor vessels by angiogenesis inhibitors leads to no
change on or reduced total functional blood vessels in tumors and resulting in no change
on or decreased cytotoxic drugs transport. Even in the tumor vasculature normalization
window, decreases in vessel permeability to cytotoxic drugs may overwhelm the
favorable changes in vessel morphology for drug penetration and result in reduced drug
levels in tumors as evidenced and discussed by Devineni [145]. Only the favorable
effects on drug transport overweighting the unfavorable effects will result in an increase
in drug transport capacity of the tumor vasculature and microenvironment. Increasing the
total number of functional blood vessels, increasing the blood perfusion and decreasing
the interstitial pressure are examples of the favorable effects, while reducing the blood
vessel permeability and decreasing the total blood vessels are examples of the
unfavorable effects. The observation of the decreased intratumoral TMZ concentration
and penetration by Gallo et al. in rat glioma model is correlated to the decreased MVD in
tumor. Thus the decreased intratumoral concentration of TMZ may due to the
15

over-pruned microvessel [146, 147]. In contrast, the increased intratumoral TMZ
concentration and penetration is significantly correlated to the VNI of the tumor [51,
148]. This increased intratumoral TMZ concentration is likely due to the proper tumor
vasculature normalization. Thus defining the tumor vasculature normalization window
and favorable effects of anti-angiogenic agents on the penetration of cytotoxic drugs into
solid tumors is difficult, but crucial for the success of the combination of the
anti-angiogenic agents and cytotoxic drugs regimen.
1.5.2 The effects of BEV on cytotoxic drugs disposition in solid tumors
No publications have estimated the effect of BEV on cytotoxic drug penetration in
solid tumors for clinical patients, but several papers [152, 153] demonstrate that there is
no pharmacokinetic interaction between BEV and cytotoxic drugs in the plasma of
patients with solid tumors. Thus in this section, we will only discuss the effects of BEV
on cytotoxic drugs disposition in solid tumors evaluated in preclinical studies.
In preclinical studies, Yanagisawa [49] demonstrated that the co-administration of
BEV significantly increased the intratumoral paclitaxel concentration in both murine
MX-1 human breast cancer and A547 human lung cancer xenograft models. Recently,
We also evidenced that the intratumoral penetration of TPT was enhanced as much as
81% when given 1 to 3 days after BEV, compared with when both drugs were given
concomitantly, or 7 days apart in neuroblastoma xenografts [154]. In consistent with this
observation, tumor vasculature normalization was observed within 7 days after BEV
administration and antitumor activity was also significantly enhanced when administering
TPT 3 days after BEV compared to monotherapy or concomitant administration of the
two drugs. The increased intratumoral penetration of TPT was closely associated with
normalization of the tumor vasculature. Furthermore, Davidoff (St. Jude Children’s
Research Hospital, Memphis, TN) found that the tumor vasculature normalization
window occurred between 2 to 5 days after BEV administration in the murine Rh30
rhabdomyosarcoma xenograft, and the treatment with ionizing radiation 2 or 5 days after
BEV resulted in the greatest antitumor activity [155]. In order to further investigate
whether there is a similar effect of BEV on TPT penetration in this Rh30 xenograft and
whether an optional schedule of the BEV and TPT will lead to enhanced tumor
inhibition, we proposed the current project to answer above questions and ultimately
benefit children with rhabdomyosarcoma cancer by providing a better chemotherapy
regimen. As discussed above, ARMS has a relatively low OS rate and is resistant to TPT
treatment. If we can identify the optimal schedule of BEV and TPT, and enhance the
intratumoral penetration and efficacy of TPT by using preclinical model, we may be able
to design proper clinical trials to confirm the preclinical findings and improve the OS rate
for children with ARMS.
16

1.6 Pharmacokinetic Models of TPT in Preclinical Studies
Extensive preclinical pharmacokinetic studies for TPT have been published over
the last 20 years [156-161]. Among these publications, numerous pharmacokinetic
models either for in vitro intracellular TPT uptake and kinetics [156, 157] or for an in
vivo pharmacokinetic model and effective schedule of TPT in human cancer xenografts
[158-161] were proposed by several groups. Our discussion focuses mainly on TPT
pharmacokinetic evaluation in preclinical animal models, including rodents and
nonhuman primates.
In order to better define the pharmacokinetic behavior of TPT in both plasma and
cerebrospinal fluid (CSF) and to measure TPT CSF penetration, Blaney et al. [159]
performed a pharmacokinetic study of TPT in 3 adult male rhesus monkeys after an
intravenous dose of 10 mg/m 2 administered over 10 minutes and used a relative simplistic
non-compartmental model to get the pharmacokinetic parameters. The CSF concentration
peaked at 30 minutes after administration and the CSF penetration of TPT exceeded 30%,
which warranted the further study in patients with high risk or refractory central nervous
system tumors. In a more pharmacokinetically elegant analysis, Balthasar’s group from
The State University of New York published two mathematical models of TPT in mice.
The first one [158] described an integrated pharmacokinetic/toxicodynamic model to
characterize the relationship between the TPT disposition and TPT induced toxicity.
Body weight loss was used as the index of TPT-induced toxicity. The authors fitted four
models composed of two disposition compartments and one peritoneal absorption
compartment to the plasma concentration data, but with different kinetics of TPT
absorption and elimination. A modified indirect response toxicity model was combined
with the best fitting pharmacokinetic model selected from those four pharmacokinetic
models. Four additional transit compartments were added to account for the delay of the
time of maximum plasma TPT concentration and the time associated with the nadir body
weight. The same group published a second paper regarding mathematical model of TPT
in mice is a whole body physiologically based pharmacokinetic model to characterize and
predict TPT concentrations in mouse plasma and tissues, such as lungs, heart, muscle,
liver and brain [160].
Moreover, tremendous work on the pharmacokinetic study and mathematical
model of TPT has been published from our laboratory [162-166]. The traditional
pharmacokinetic model used in the lab to describe the plasma and target tumor drug
concentration used a non-linear three compartmental model including central
compartment, peripheral compartment and tumor compartment. In this model, plasma
TPT concentration–time profile was fit to a two-compartment model using a maximum a
posteriori (MAP) Bayesian algorithm as implemented in ADAPT 5[162, 167-169]. With
the plasma pharmacokinetic parameters remaining fixed, a third compartment was added
to represent the tumor disposition of TPT and the parameters describing the TPT tumor
concentrations were estimated for each study by using the maximum likelihood approach.
17

1.7 Summary
Although the overall survival rate for RMS is encouraging, the prognosis for
patients with relapsed or metastatic RMS at diagnosis is very poor, especially for ARMS.
Recently, antiangiogenesis agents have gained more attention due to their pivotal role in
the modulation of tumor vasculature, especially RMS.
One of the biggest obstacles for chemotherapy is the insufficient delivery of
cytotoxic drugs to their target tissue or tumor sites. The development of antiangiogenesis
agents expands the treatment modality of chemotherapy. Tumor progression and
metastases are highly dependent on angiogenesis to gain sufficient oxygen and nutrients.
VEGF is a key regulator of tumor angiogenesis and anti-VEGF monoclonal antibody,
BEV, has shown enhanced anti-tumor activity in several tumor models when combined
with conventional cytotoxic drugs. One of the mechanisms for the improved antitumor
activity in combination therapy is BEV is able to normalize tumor vasculature by
increasing the number of functional blood vessels in tumor, enhancing blood perfusion
rate and decreasing interstitial pressure, and further increase the cytotoxic drug
penetration into tumor. The schedule of combination therapy is crucial to catch the tumor
vasculature normalization window and enhance the cytotoxic drug penetration. However,
there is little known about the optimal schedule when BEV combining with conventional
cytotoxic drugs.
TPT is one of the cytotoxic drugs used in patients with RMS. Like most other
cytotoxic drugs, in order to exert its cytotoxic effect TPT has to reach tumor cells and
further entering its targeting site-nucleus. The aberrant tumor vasculature, heterogeneous
vessel walls and compacted extracellular space impedes TPT accessing tumor cells,
resulting less drugs remaining to the targeting site. Our previous work showed that the
intratumoral penetration of TPT was significantly enhanced after 3 day pre-treatment
with BEV and the increased intratumoral penetration of TPT was closely associated with
normalization of the tumor vasculature in neuroblastoma xenografts. In addition, BEV
was shown to transiently normalize tumor vasculature in Rh30 RMS xenograft between 2
to 5 days. This work rationalizes the further evaluation of the time dependent effect of
BEV on the penetration, pharmacokinetics and efficacy of TPT in Rh30 RMS xenograft.
In vivo microdialysis techniques are an invaluable tool for sampling unbound free
drugs in tumor ECF and having the proper pharmacokinetic model is a pre-requisite to
evaluate TPT penetration and pharmacokinetics in vivo. Combining microdialysis and
pharmacokinetic modeling is an excellent way to assess the pharmacokinetics of drugs in
target tissue.
18

1.8 Specific Aims
Inhibition of VEGF can transiently normalize tumor vasculature and improve
delivery of systemic chemotherapy. BEV, an anti-VEGF antibody, has been shown to
transiently normalize tumor vasculature in an Rh30 orthotopic rhabdomyosarcoma
xenograft model. However, the effects of BEV on the pharmacokinetics of TPT and the
antitumor activity of TPT have not been evaluated in this tumor model.
Specific aim 1: determine whether TPT pharmacokinetics was dependent upon the
schedule of BEV and TPT.
Specific aim 2: assess whether the combination and schedule of TPT and BEV
contributed to differential antitumor activity in the Rh30 mouse model.
19

CHAPTER 2. THE EFFECT OF BEVACIZUMAB ON THE
PHARMACOKINETICS OF TOPOTECAN IN A RH30
RHABDOMYOSARCOMA XENOGRAFT
2.1 Introduction
In order to gain sufficient nutrients and oxygen for growth, tumor cells secret and
recruit pro-angiogenic factors for the creation and maintenance of the vascular network in
solid tumors [14]. As a result, the tumor vasculature is chaotic, the blood vessel walls are
heterogeneous and the microenvironment is compact and has an interstitial hypertension
and aberrant metabolic environment─all of which can be restored by anti-angiogenic
treatments [6, 31, 53, 170]. VEGF is a key regulator of tumor angiogenesis [65, 66, 69].
It helps recruit of bone-marrow-derived progenitor cells to the primary and metastatic
sites to form a new vascular network to stimulate tumor growth. In addition, VEGF not
only promotes proliferation, migration, and invasion of endothelial cells to maintain
tumor vessel growth, but also inhibits endothelial cell apoptosis to facilitate tumor vessel
survival. Furthermore, the overexpression of VEGF is frequently observed in human
solid tumors, which is found to correlate with the extent of tumor angiogenesis,
progression and survival in patients [67, 68]. Thus, inhibiting VEGF represents a rational
strategy in treating various malignant tumors.
Rhabdomyosarcoma is the most common soft tissue sarcoma among children 0-14
years, representing nearly 50% of soft tissue sarcomas [171]. The two most common
pathologic types of RMS are embryonal RMS (ERMS) and alveolar RMS (ARMS) with
differential incidence, age pattern and body sites of occurrence [102]. ARMS grow more
aggressively than ERMS and require more intensive treatment. Therefore they have a
higher relapse incidence and worse prognostic outcome [109]. The 5 year failure-free
survival rate for ARMS (65%) is much lower than ERMS (82%) [172]. In addition, 30%
of young patients experience recurrence and 50% to 95% of these patients die of
progressive disease, even with intensified treatment [112]. So developing new agents or
new strategies to increase current agent efficacy is urgent for the treatment of RMS,
especially ARMS.
Bevacizumab (BEV) is a humanized monoclonal antibody that inhibits VEGF and
currently used to treat various cancers, including colorectal, lung, breast, kidney cancers,
and glioblastoma [173]. It is also in clinical trials for the treatment of RMS in
combination with traditional cytotoxic chemotherapy [174, 175]. However, the effect of
dosing schedule of BEV in combination with cytotoxic drugs is not well understood. The
Rh30 cell line retains the histologic appearance of ARMS [176]. VEGF is over-expressed
in the Rh30 cell line and anti-VEGF treatment has been shown to inhibit the growth of
Rh30 RMS xenograft [115]. The Rh30 cell line is more sensitive to Topotecan (TPT)
than RD cell line, characterized as ERMS cell line [116]. TPT has been actively
investigated in clinical trials and had an encouraging response rate in ARMS patients
[177]. However, preclinical and clinical studies showed that RMS is resistant to TPT as
20

most cytotoxic drugs [118, 119]. One approach to overcome the drug resistant and
increase its efficacy is to increase its intratumoral concentration of TPT.
Our previous work [154] has shown that BEV enhanced the penetration of TPT in
orthotopic neuroblastoma xenografts possibly due to the transiently normalized tumor
vasculature. In addition, BEV [155] has been shown to transiently normalize tumor
vasculature in murine Rh30 rhabdomyosarcoma xenograft. Therefore, we hypothesized
that the normalized tumor vasculature by BEV would facilitate the penetration of TPT in
Rh30 RMS xenograft. The specific aim 1 of this project was to determine whether TPT
pharmacokinetics was dependent upon the schedule of BEV and TPT. The specific aim 2
was to assess whether the combination and schedule of TPT and BEV contributed to
differential antitumor activity in the Rh30 mouse model.
2.2 Materials and Methods
2.2.1 Materials and chemicals
TPT (Hycamtin, GlaxoSmithKline, Philadelphia, PA) was prepared in sterile
saline for injection at a concentration of 0.4 mg/ml. BEV (Avastin, Genentech, South San
Francisco, CA) was diluted in sterile saline right before injection from stock
concentration of 25 mg/ml to 1 mg/ml. Isoflurane (Forane) was purchased from Baxter
Pharmaceutical Products (New Providence, NJ). Acetonitrile and triethylamine were of
high-performance liquid chromatography (HPLC) grade. All other chemicals and
solvents used were of analytic grade or better.
2.2.1 Cell culture
The Rh30 pediatric RMS cell line was kindly provided by Dr. Davidoff
(Department of Surgery, St. Jude Children’s Research Hospital) and was grown as a
monolayer in RPMI 1640 medium (Life Technologies Inc., Gaithersburg, MD)
supplemented with 10% fetal bovine serum. When cells reached 80-90% confluency,
they were collected, counted, and resuspended in phosphate-buffered saline (PBS)
solution to prepare a cell suspension of 1×10 4 cells/ μL for tumor inoculation.
2.2.3 Animals
4 to 6-week-old female CB-17 SCID mice were purchased from Charles River
Laboratories (Wilmington, MA). The mice were maintained on a 12 hour light/dark cycle
with access to food and water ad libitum. All procedures were performed in accordance
with a protocol approved by the Institutional Animal Care and Use Committee at St Jude
Children's Research Hospital.
21

2.2.4 Tumor model and treatment
Orthotopic ARMS xenograft was established as previously described by Dr.
Davidoff [155]. Briefly, 2 × 10 6 Rh30 tumor cells suspended in 200 μL PBS were
injected into the right calf muscle of female CB-17 SCID mice. Intramuscular tumor size
was estimated by measuring the size of the normal left calf and subtracting that volume
(width 2 × length× 0.5) from the volume of the tumor-injected right calf.
Microdialysis studies were performed to address the specific aim 1. After
approximately 4 weeks of tumor growth, mice were divided into 4 groups of equivalent
tumor burden (~700 mm 3 ) and treatment was initiated. Six to eight mice per group were
pretreated with either vehicle control or a single dose of 5.0 mg/kg BEV intravenously at
1 hour (vehicle control), 1 day, 3 days or 7 days before the tail vein injection of TPT (2.0
mg/kg). Using a previously described limited sampling strategy [178], we bled each
mouse from the retro-orbital plexus 15, 60, and 180 min after the IV injection of TPT to
assay total TPT in plasma. Tumor extracellular fluids were collected up to 6 hours by
microdialysis. For TPT the pharmacokinetics studies after multiple doses of BEV
administration, treatments were initiated when the tumor burden approached
approximately 200 mm 3 . Six to eight mice per group were treated with BEV or vehicle
twice weekly for total 4 doses before TPT administration. TPT was injected 1 hour
(vehicle control), 1 day, 3 days or 7 days after the last dose of vehicle or BEV
administration. Plasma was collected at 15, 60 and 180 min after TPT IV injection and
tumor extracellular fluids were collected up to 6 hours by microdialysis.
The antitumor activity after SDBT and MDBT were evaluated to address the
specific aim 2. In the SDBT groups, a cohort of tumor-bearing mice was divided into 4
groups when the tumor burden was approximately 700 mm 3 . Five to six mice were
treated with BEV only, TPT only, BEV given 1 day before TPT and BEV given 7 days
before TPT. The final tumor volume in mice treated with BEV only and received TPT 1
day or 7 days after BEV were evaluated to assess whether the addition of TPT had effect
on antitumor activity of BEV. Similarly, the final tumor volume in mice treated with TPT
only and received TPT 1 day or 7 days after BEV were evaluated to assess whether the
pre-treatment of BEV has effect on antitumor activity of TPT. Furthermore, the final
tumor volume in mice treated with TPT 1 day and 7 days after BEV administration were
evaluated to assess whether the antitumor activity was dependent upon the schedule of
BEV and TPT. Nonparametric student's t-test was used for two group comparisons.
Comparison of more than two groups was done by one way ANOVA and followed by
Newman Keuls multiple comparison post hoc procedure if there was significant
difference between groups. In the MDBT groups, the same cohorts of mice were used for
the pharmacokinetics studies and the efficacy studies. An additional BEV only group was
added for the efficacy study as monotherapy control. As the tumor burden was
approximately 200 mm 3 , six to eight mice treated with BEV only, TPT only, TPT given 1
day, 3 days or 7 days after the last dose of BEV were evaluated for the efficacy studies.
The final tumor volume in mice treated with BEV only and received TPT 1 day, 3 days or
7 days after the last dose BEV were evaluated to assess whether the addition of TPT has
effect on antitumor activity of BEV. Similarly, the final tumor volume in mice treated
22

with TPT only and received TPT 1 day, 3 days or 7 days after the last dose of BEV were
evaluated to assess whether the pre-treatment of BEV has effect on antitumor activity of
TPT. In addition, the final tumor volume in mice treated with TPT 1 day, 3 days or 7
days after the last dose of BEV administration were evaluated to assess whether the
antitumor activity was dependent upon the schedule of BEV and TPT.
Collectively, the TPT penetration and efficacy study designs were shown in
Tables 1-2 and Figures 1-2.
2.2.5 In vivo tumor microdialysis
The principle and methodology of microdialysis sampling have been reviewed
thoroughly in volume 45, issue 2-3 of Advanced Drug Delivery Reviews. In brief, a short
length of semi-permeable microdialysis probe is implanted into tissue and continuously
perfused with a physiologic solution at a low flow rate (0.5-10 µl/min). The analyte of
interest in the tissue ECF diffuses into the microdialysis probe, resulting from the
concentration gradient across the probe membrane, and is carried via microtubing into the
collection vials.
In the present study, a CMA/20 microdialysis probe (CMA Microdialysis,
Chelmsford, MA) was used. The probe was perfused with Ringer's solution (USP) at 0.5
μL/min flow rate by a CMA 102 pump (CMA Microdialysis, Chelmsford, MA). The
probe was equilibrated for one hour prior to the microdialysis sample collection. The
dialysate samples were collected up to 6 hours every 30 minutes for the off line system
and every 18 minutes for the online system [179] after TPT injection. The off line system
was composed of two steps─collecting samples manually and analyzing samples on a
separate HPLC system, while the samples were directly injected into a connected HPLC
system and analyzed at real-time on the on line system [179]. The samples were stored in
the -80°C freezer before analysis for the off line system.
For each microdialysis experiment, retrodialysis calibration was performed as
previously described [178] after the sample collection. Briefly, a TPT solution (50
ng/mL) was prepared in Ringer’s solution and perfused through the microdialysis probe
at two different flow rates 4.0 and 0.5 μL/min. The system was allowed to equilibrate for
30 minutes between the flow rate change. The total TPT concentration in the solution
exiting the probe at 4.0 μL/min (Cin) and at 0.5 μL/min (Cout) was determined by HPLC.
The recovery was estimated as shown in Equation 1.
Recovery % TPT C C
C
100 Eq. 1
At the end of the retrodialysis study the mice were euthanized by cervical
dislocation under anesthesia.
23

Table 1.
(SDBT)
TPT penetration study design after a single dose of BEV treatment
Groups T 1D BT 3D BT 7D BT
BEV
(5 mg/kg)
Vehicle IV
Day 0
Single IV
Day 0
Single IV
Day 0
Single IV
Day 0
TPT
(2 mg/kg)
Single IV
Day 0
Single IV
Day 1
Single IV
Day 3
Single IV
Day 7
Treatment was initiated when tumor burden was approaching approximately 700 mm 3
and four groups were evaluated: group T received a single dose of vehicle 1 hour before
TPT; group 1D BT received a single dose of BEV 1 day before TPT; group 3D BT
received a single dose of BEV 3 days before TPT; group 7D BT received a single dose of
BEV 7 days before TPT.
Table 2.
(MDBT)
TPT penetration study design after multiple doses of BEV treatment
Groups mT 1D mBT 3D mBT 7D mBT
Vehicle IV Multiple IV Multiple IV Multiple IV
BEV
Day -10, -7, Day -10, -7, Day -10, -7, Day -10, -7,
(5 mg/kg)
-3, 0
-3, 0
-3, 0
-3, 0
TPT
(2 mg/kg)
Single IV
Day 0
Single IV
Day 1
Single IV
Day 3
Single IV
Day 7
Treatment was initiated when tumor burden was approaching approximately 200 mm 3
and four groups were evaluated: group mT received four doses of vehicle and TPT was
given 1 hour after the last dose of vehicle; group 1D mBT received four doses of BEV
and TPT was given 1 day after the last dose of BEV; group 3D mBT received four doses
of BEV and TPT was given 3 days after the last dose of BEV; group 7D mBT received
four doses of BEV and TPT was given 7 days after the last dose of BEV.
24

Figure 1.
TPT efficacy study design after SDBT
Treatment was initiated when tumor burden was approaching approximately 700 mm 3 .
Group B received a single dose of BEV and groups T, 1D BT and 7D BT received some
therapeutic regimen as Table 1. Tumor volume was measured at the beginning of the
treatment and two weeks after the treatment at day 40. BEV injection shown as ; TPT
injection shown as ; tumor measurements shown as .
25

Figure 2.
TPT penetration plus efficacy study design after MDBT
Treatment was initiated when tumor burden was approaching approximately 200 mm 3 .
Group mB received four doses of BEV only and all other groups are the same as in Table
2. Microdialysis study was performed on the day of TPT administration and tumor
volume was measured at the beginning of the treatment and 24 days after the treatment.
BEV injection shown as ; vehicle injection shown as ; TPT injection shown as ; tumor
measurements shown as .
26

2.2.6 High-performance liquid chromatography analysis for PK studies
Total TPT in plasma and tumor ECF were measured as previously described [165,
180]. 20 μL plasma aliquots were added to 80 μL cold methanol (−30°C). Samples were
vortex mixed vigorously and centrifuged at 10,000 rpm for 2 minutes. TPT in the plasma
methanolic supernatants and tumor ECF were converted to total TPT by adding five parts
methanolic supernatant or tumor ECF to one part 20% phosphoric acid and injected into
HPLC with fluorescence detection. The unbound plasma TPT concentration was
calculated on the basis of a previous study [178], showing a 30.1% unbound fraction in
CB-17 SCID mice. All TPT concentrations reported in this study were the total unbound
TPT concentration.
2.2.7 Pharmacokinetic model evaluation
Different PK models were considered to describe the TPT concentrations in
plasma and tumor ECF: (1) a three compartmental PK model previously used in our lab
(Figure 3) [162, 165, 169]; (2) we also evaluated other multi-compartmental models
during the data analysis. The final modified multi-compartmental PK model is shown in
Figure 4.
The modified multi-compartmental PK model significantly improved the
estimation of PK parameters describing TPT in tumor compartment compared to the
conventional model. This general model can be applied for drug administration via orally,
IP or IV bolus. The model has an absorption compartment, a central and a peripheral
compartment, and a tumor compartment. Additionally, two transient compartments
between the plasma and tumor compartments were incorporated to account for the delay
of drug transport from plasma to tumor compartment. The differential equations are
shown in Equations 2-7. Model parameters estimated for intravenous dosing included
elimination rate constants (Ke is systemic elimination rate constant; Kcp, Kpc and Kct
are intercompartment rate constants; Kte is elimination rate constant for TPT leaving
tumor compartment) and the volume of distribution in central compartment (Vc) and
tumor compartment (Vt). The secondary parameters were determined: CLin = Kct × Vc
and CLout = Kte × Vt. The independent rate constants between the transient
compartments were not identifiable and were set to the elimination rate constant Kct. All
volume units are described in liters/m 2 and all elimination rates are described in hour -1 .
Eq. 2
Eq. 3
Eq. 4
Eq. 5
27

Figure 3.
A pharmacokinetic model for TPT
Figure 4.
The modified multi-compartmental PK model for TPT
28

Eq. 6
Eq. 7
The variables X1, X2, X3, X4, X5 and X6 are to the drug amounts in the central,
absorption, peripheral, two transient compartments and tumor compartments; Ke is
systemic elimination rate constant; Kcp and Kpc are intercompartment rate constants
between peripheral and central compartments; Kct is elimination rate constant from
central compartment to tumor compartment; Kte is elimination rate constant leaving from
tumor compartment; Vc is volume of distribution in central compartment and Vt is
volume of distribution in tumor compartment.
2.2.8 Population pharmacokinetic analysis
Non linear mixed effects modeling using the MLEM algorithm implemented in
ADAPT 5 [181] was used to evaluate the TPT plasma and tumor ECF concentrations. In
the MLEM algorithm, ML is combined with an EM algorithm. The EM algorithm
consists of two steps. In the first step, each individual’s parameters are estimated using
the latest predicted parameter values and the observed data. In the second step, parameter
values are updated to maximize the log-likelihood function in the first step. These two
steps are then iterated until convergence. The initial values for population means and
population covariance matrix (inter-individual variability) were estimated by naïve
pooled analysis. Both population and individual estimates ware determined. The
model-fitted curve for each mouse was used to estimate the area under the
concentration-time curve from time zero to 6 hr in plasma (AUCp) and tumor ECF
(AUCt). The measures of penetration were expressed as AUC tumor-to-plasma ratio
(AUCt/AUCp).
2.2.9 Covariate analysis
A diagnostic screening was done to identify covariates such as the presence of
BEV in the treatment and the different schedules of the combination therapy that
potentially affected TPT PK parameters, including systemic elimination rate Ke,
elimination rate from tumor compartment Kte and volume of distribution in tumor
compartment Vt. These potential covariates were then included in the non-linear
mixed-effects population model to investigate their ability to significantly improve the
model fit (by a reduction of at least 3.84 [p

2.2.10 Statistical analyses
For each mouse, a TPT tumor-to-plasma AUC ratio was calculated and summary
statistics (mean, standard deviation and the variation coefficient) were used to describe
the TPT penetration results for each treatment group. Nonparametric student's t-test was
used for two group comparisons. Comparison of more than two groups was done by one
way ANOVA and followed by Newman Keuls multiple comparison post hoc procedure if
there was significant difference between groups. P values less than 0.05 indicated
statistical significance.
2.3 Results
2.3.1 The effect of BEV on the pharmacokinetics of TPT
We studied the intratumoral penetration of TPT after combining either single dose
of BEV or multiple doses of BEV with different schedule. The TPT concentration-time
profiles in plasma and tumor from representative mice is depicted in Figure 5 (SDBT)
and Figure 6 (MDBT). The TPT AUCt, AUCp and AUCt/AUCp for each treatment
group are shown in Table 3 and Figure 7 (SDBT) and Table 4 and Figure 8 (MDBT).
One way ANOVA multiple group comparisons indicated that there was no significant
difference in the plasma exposure between groups after SDBT (p=0.5388) and in the
intratumoral exposure, plasma exposure and intratumoral penetration of TPT between
groups after MDBT (p=0.297, p=0.932 and p=0.307, respectively). However,
pre-treatment of single dose BEV showed a trend toward higher intratumoral exposure
(p=0.0610) and penetration (p=0.0662) of TPT given 1 day after BEV administration
compared to either TPT given alone or TPT given 3 days and 7 days after BEV.
However, the power for distinguishing the intratumoral exposure and penetration of TPT
between group T and group 1D BT at significance level 0.05 is as low as 6.97% and
31.6%, while the power for distinguishing the intratumoral exposure and penetration of
TPT between group T and group 7D BT at significance level 0.05 are 53.9% and 82.8%.
The population PK parameters obtained for each treatment group are listed in
Table 5 (SDBT) and Table 6 (MDBT). Based on visual inspection of the parameters,
there is substantial variability in TPT pharmacokinetics between SDBT groups. As
depicted in Figure 9, covariate analysis indicated that SDBT correlated with higher
systemic elimination (Ke) of topotecan and the elimination rate from tumor compartment
(Kte) also associated to the different treatment schedule between TPT and BEV. One day
SDBT significantly increased TPT elimination rate from tumor compartment and after 3
or 7 days’ SDBT, TPT elimination rate from tumor compartment decreased to the level
without SDBT. Specifically, when BEV was incorporated in the model for Ke, a
significant reduction in negative log-likelihood (-109) was observed (p

Figure 5. Representative plasma and tumor disposition of TPT with/without
SDBT in mice bearing Rh30 RMS xenograft
Representative unbound TPT concentration-time plots in tumor ECF ( ) and plasma ( )
in Rh30 rhabdomyosarcoma xenograft mice were shown above. Compared to the three
compartmental PK model, the modified multi-compartmental PK model significantly
(p

Figure 6. Representative plasma and tumor disposition of TPT with/without
MDBT in mice bearing Rh30 RMS xenograft
Representative unbound TPT concentration-time plots in tumor ECF ( ) and plasma ( )
in Rh30 rhabdomyosarcoma xenograft mice were shown above. Compared to the three
compartmental PK model, the modified multi-compartmental PK model significantly
(p

Table 3.
TPT penetration after SDBT in mice bearing Rh30 RMS xenograft
Parameters AUCt (ng•hr/L) AUCp (ng•hr/L) AUCt/AUCp
Groups Mean SD CV% Mean SD CV% Mean SD CV%
T 534 76.2 14.3 153 64.1 41.8 3.79 1.13 29.7
1D BT 553 169 30.6 110 16.8 15.2 4.93 1.09 22.0
3D BT 339 104 30.6 132 69.9 53.0 2.98 1.47 49.1
7D BT 353 62.6 17.7 184 101 54.7 2.17 0.700 32.4
SD refers to standard deviation and CV% refers to coefficient of variation (CV%= SD/Mean×%).
33

Figure 7. The effect of BEV on the intratumoral exposure, plasma exposure and
intratumoral penetration of TPT after SDBT in mice bearing orthotopic Rh30 RMS
xenograft
The intratumoral and plasma exposure of TPT is shown in Panel A and B. The
penetration of TPT is shown in Panel C. One way ANOVA analysis: p=0.0610 for panel
A; p=0.539 for panel B and p=0.0662 for panel C
34

Table 4.
TPT penetration after MDBT in mice bearing Rh30 RMS xenograft
Parameters AUCt (ng•hr/L) AUCp (ng•hr/L) AUCt/AUCp
Groups Mean SD CV% Mean SD CV% Mean SD CV%
mT 428 77.1 18.0 165 28.4 17.2 2.68 0.859 32.0
1D mBT 519 161 31.0 169 29.0 17.1 3.06 0.787 25.7
3D mBT 370 180 48.7 154 52.9 34.3 2.40 0.673 28.0
7D mBT 516 144 27.8 168 51.0 30.3 3.17 0.787 24.8
SD refers to standard deviation and CV% refers to coefficient of variation (CV%= SD/Mean×%).
35

Figure 8. The effect of BEV on the intratumoral exposure, plasma exposure and
intratumoral penetration of TPT after MDBT in mice bearing orthotopic Rh30
RMS xenograft
The intratumoral and plasma exposure of TPT is shown in Panel A and B. The
penetration of TPT is shown in Panel C. One way ANOVA analysis: p=0.297 for panel
A; p=0.931 for panel B and p=0.307 for panel C
36

Table 5.
Population PK parameters of TPT estimated after SDBT
Groups # T 1D BT 3D BT 7D BT
Parameters Mean SD IIV Mean SD IIV Mean SD IIV Mean SD IIV
Ke (1/h) 0.448 0.120 26.7 1.51 0.760 50.3 1.07 0.819 76.6 1.06 0.804 76.0
Vc (L/m 2 ) 14.1 3.71 26.2 12.7 6.66 52.4 13.7 9.33 68.2 12.6 6.93 54.8
Kcp (1/h) 0.627 0.448 71.4 1.59 1.57 99.2 1.32 1.33 100 0.604 0.700 116
Kpc (1/h) 0.588 0.0600 10.2 0.344 0.0987 28.6 0.791 0.631 79.7 0.667 0.0600 9.00
Kct (1/h) 2.11 0.395 18.7 1.48 0.288 19.5 1.83 0.706 38.6 1.42 0.194 13.6
Kte (1/h) 4.61 1.04 22.5 16.3 7.07 43.4 6.03 3.56 59.1 6.45 0.500 7.74
Vt (L/m 2 ) 2.12 0.239 11.3 0.307 0.173 56.4 1.78 1.36 76.6 1.50 0.399 26.6
MLEM program was used in this population modeling for each individual group. Mean and SD refer to population mean and
population standard deviation; IIV refers to inter-individual variability as of %CV.
37

Table 6.
Population PK parameters of TPT estimated after MDBT
Groups # mT 1D mBT 3D mBT 7D mBT
Parameters Mean SD IIV Mean SD IIV Mean SD IIV Mean SD IIV%
Ke (1/h) 0.825 0.505 61.2 0.371 0.323 87.0 0.284 0.211 74.4 0.343 0.392 114
Vc (L/m 2 ) 9.61 2.22 23.1 8.81 2.24 25.5 11.2 5.01 44.6 10.8 7.97 73.7
Kcp (1/h) 1.35 1.61 119 4.93 1.30 26.3 4.06 1.43 35.3 1.88 2.82 150
Kpc (1/h) 0.795 0.538 67.7 0.966 0.471 48.8 1.14 0.891 78.1 0.602 0.383 63.6
Kct (1/h) 1.93 0.532 27.6 1.68 0.630 37.4 2.10 0.842 40.2 1.66 0.995 60.0
Kte (1/h) 15.8 10.1 63.9 11.3 8.54 75.4 15.3 18.9 124 14.0 10.7 76.2
Vt (L/m 2 ) 0.580 0.467 80.5 0.611 0.549 89.8 0.791 1.13 143 0.501 0.424 84.6
MLEM program was used in this population modeling for each group. Mean and SD refer to population mean and population standard
deviation; IIV refers to inter-individual variability as of %CV
38

Figure 9.
The effect of treatment regimen on Ke and Kte
A: Higher Ke associated with SDBT; B: Differential Kte associated with the timing of
SDBT.
39

variability for Kte decreased from 308%to 162%. However, the pharmacokinetic analysis
showed that the use of MDBT had no effect on the pharmacokinetics of TPT in plasma
and tumor compartment.
The results of this analysis indicated that SDBT was associated with higher
systemic elimination rate of TPT given after BEV compared to TPT given alone. In
addition, the elimination rate of TPT from tumor compartment was dependent upon the
schedule of BEV and TPT: increased after 1 day treatment of BEV and gradually
decreased after 3 days and 7 days treatment of BEV. SDBT did produce a trend toward
higher intratumoral exposure and penetration of TPT given 1 day after BEV
administration compared to either TPT given alone or TPT given 3 days and 7 days after
BEV, however, the current experiment had a low power to identify the significant
increase in intratumoral exposure and penetration of TPT after 1 day pre-treatment of
BEV.
2.3.2 The antitumor activity of the combination therapy
In the SDBT groups, as shown in Figure 10, TPT significantly enhanced the
antitumor activity of BEV when comparing final tumor volume between group B vs
groups 1D BT (mean±SD: 1525±322 vs 1019±199, p

Figure 10. The effect of different schedule of SDBT combined with TPT on the
growth of orthotopic Rh30 tumors.
Mice were size matched at day 26 (black columns) and tumor volume was measured after
treatment at day 40 (gray columns). **, p = 0.01 comparing the final tumor volume in
mice treated with TPT 1 day or 7 days after BEV with mice that received BEV only.
41

Figure 11. The effect of different schedule of MDBT combined with TPT on the
growth of orthotopic Rh30 tumors.
Treatment was initiated when tumor volume reached approximately 200 mm 3 at day 21
(black columns). Tumor volume was measured after treatment at day 45 (gray columns).
**, p = 0.01 comparing the final tumor volume in mice treated with BEV only with mice
that received TPT only. **, p = 0.01 comparing the final tumor volume in mice treated
with TPT 1 day or 3 days after BEV with mice that received TPT only. *, p = 0.05
comparing the final tumor volume in mice treated with TPT 7 days after BEV with mice
that received TPT only.
42

CHAPTER 3.
DISCUSSION AND CONCLUSIONS
The combination of angiogenesis inhibitors and cytotoxic drugs are currently
investigated because of their different cellular targeting and non-overlapping toxicity of
these two class drugs, and the encouraging response in preclinical studies and clinical
trials [49, 51, 154, 182, 183]. However, the optimal scheduling and dosing of the
combination is not well defined and has a pivotal role in the success of this regimen [14,
146]. Furthermore, the potential role of angiogenesis inhibitors in cytotoxic penetration
and pharmacokinetic changes is also unclear and controversial [91, 147]. BEV is one of
the better angiogenesis inhibitors due to its prevailing benefits in facilitating cytotoxic
drugs treatment. TPT is ARMS-sensitive drug and currently used in treatment of RMS,
however, as most cytotoxic drugs, clinical trials showed RMS is also resistant to TPT.
One of the strategies to overcome drug resistance is to increase the intratumoral
concentration and BEV administration has been proposed as a pharmacological means to
normalize tumor vasculature and thereby enhance TPT penetration. This is the first study
to determine the optimal scheduling of BEV and the cytotoxic drug TPT in the treatment
of ARMS and to assess the effect of BEV on the pharmacokinetics and antitumor activity
of TPT.
First, we conducted microdialysis studies to obtain total unbound TPT
concentration in tumor ECF and plasma after TPT combined with a single dose or
multiple doses of BEV at different schedule. We used a three compartmental PK model
previously used in our lab to predict TPT concentration-time profiles in tumor ECF and
plasma as well as PK parameters for individual mouse. However, the model poorly
predicted the TPT concentration in tumor ECF with large –log likelihood. In addition, the
PK parameters from this conventional model were always with huge variability. In order
to better predict the concentration-time profile in tumor ECF and accurately describe the
PK of TPT, we modified the conventional model. The modified PK model in Figure 4
significantly improved the model fit with a significant reduction of –log likelihood for
each mouse and the variability of predicted PK parameters were within reasonable range
(CV%

efflux transporters. TPT is a camptothecin and topoisomerase I inhibitor [184-186] and
undergoes both renal and hepatic elimination [167, 187]. TPT is a substrate of efflux
transporters such as P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP)
[168, 188]. Although no publications have shown efflux transporters are blocked by
macromolecular antiangiogenic agents, but only by small molecular angiogenesis
inhibitors [189-192], a recent paper published this year [193] has indicated that there was
a significant negative correlation between VEGF level and creatinine clearance. A
decreasing VEGF level may increase creatinine clearance, especially for patients with
impaired renal function that is associated with elevated angiogenic growth factors such as
VEGF, VEGF receptors, Ang-1 and Ang-2. Thus SDBT may induce the renal clearance
of TPT and affect the systemic elimination rate and clearance of TPT.
PK modeling also indicated that TPT elimination from the tumor compartment
was significantly increased after 1 day of a single dose BEV treatment and gradually
decreased to the control level after 3 days and 7 days of a single dose BEV
administration. This observation supports the concept of vascular normalization proposed
by Jain [14]. The vasculature in solid tumors is structurally and functionally
abnormal[14] and lymphatic vessels also become dysfunctional, resulting in interstitial
hypertension in solid tumors caused by lack of a drainage system [17, 22]. Consequently,
cytotoxic drugs that have been delivered to the tumor compartment could be confined in
the tumor and a reduction in elimination rate of the cytotoxic drugs from the tumor
compartment is expected. Blocking angiogenesis leads to elimination of immature blood
vessels and relief of the tumor microenvironment stress [50, 194]. Normalization of the
lymphatic system was also documented by several studies [195, 196]. One of the possible
mechanisms for the increased TPT tumor elimination after 1 day of BEV treatment could
be the normalization of blood vessels and lymphatic system by BEV. The normalized,
functional lymphatic vessels can drain out TPT from the tumor more rapidly. As the
normalization effect of BEV diminishes over time, the lymphatic vessels lose their
transport ability again and cytotoxic drugs are restricted in the tumor and have lower
elimination rate. Additionally, the relieved interstitial hypertension could be another
contributor to the increased TPT tumor elimination. Through the transient normalization
effect of BEV, the decreased interstitial hypertension allows TPT to diffuse out from the
tumor more rapidly. But when the interstitial hypertension increases again after the
normalization effect of BEV disappears, the diffusion rate of TPT gradually decreases to
control level.
In the microdialysis studies for TPT penetration after SDBT, we observed a trend
in changes in TPT penetration. However, due to the low power of the experiment we did
not identify which schedule of the combination treatment changed the TPT penetration.
Thus in future studies, we may add more animals in each group to insure the experiment
has sufficient power to determine whether the pre-treatment of BEV may enhance the
penetration of TPT in Rh30 xenograft. Additionally, TPT penetration AUCt/AUCp was
the overall display of the pharmacokinetics of TPT in tumor and plasma compartment.
The results indicated that 1 day pre-treatment of BEV was associated with an increase in
the systemic clearance of TPT, resulting from the increased Ke and on changes on Vc,
leads to a decrease in AUCp. The covariate analysis showed that 1 day pre-treatment of
44

BEV was associated with an increase in Kte and a decrease in Vt, which may lead to an
increase in AUCt. Thus, we may expect an increase in AUCt/AUCp ratio. Indeed, the
absolute value of AUCt/AUCp was increased, but the increase did not reach a significant
level. In the microdialysis studies for TPT penetration after MDBT, we didn’t observe
difference in TPT penetration. The exact underlying mechanism is unknown but could be
due to the net balance of the anti-VEGF-induced pharmacodynamic effect on tumor
vasculature and microenvironment changes [147]. Following anti-VEGF treatment, the
tumor vasculature may undergo normalization with more functional blood vessels,
increased blood flow and perfusion and decreased interstitial pressure. The entire tumor
vasculature normalization effect following BEV administration would increase the tumor
uptake of cytotoxic drugs [91]. However, these blood vessels’ morphology and
microenvironment changes are not the sole effect caused by anti-VEGF treatment. The
anti-VEGF agent may also over prune the blood vessels and result in a substantial
decrease in blood vessel surface area and blood vessel permeability, which decreased
cytotoxic drug penetration into tumor tissue [146]. Thus after 1 day, 3 days or 7 days of
the BEV administration, the tumor vasculature underwent these pharmacodynamic
changes, and the overall effect on TPT penetration may cancel out each other─the
increased intratumoral concentration by vasculature normalization is compensated by the
deceased intratumoral concentration by over-pruning blood vessels. Moreover, for the
multiple doses of BEV groups, another factor that may contribute the observed
phenomenon is the anti-drug antibodies (ADA). Administration of therapeutic proteins
can lead to unexpected immunogenicity in recipients of these products [197]. Repeated
administration of BEV may induce the production of its ADA, and the ADA would
interfere with the target of BEV as observed in the usage of an anti-angiogenesis inhibitor
[198]. This would further result in a diminished effect on VEGF inhibition and the tumor
vasculature normalization. This explains why we didn’t see any changes in tumor
exposure and penetration of TPT after MDBT compared to no BEV treatment.
Antitumor activity after a single dose of BEV and TPT combination therapy is
superior to either agent used alone as shown in Figure 10. Currently, the prevailing
rationale for the combination therapy of anti-angiogenic agents and cytotoxic drugs is
anti-angiogenic agents induce tumor vasculature normalization and further increase
cytotoxic drug penetration and efficacy [14, 49, 154]. However, enhanced antitumor
activity can be achieved by combining the anti-angiogenic agents with cytotoxic drugs,
despite a substance decrease in tumor uptake of the cytotoxic drugs [199, 200]. In our
study, the additive effect on antitumor activity after combining BEV and TPT was
observed, yet the penetration into tumor tissue and the tumor uptake of TPT did not alter
or was even lower (T vs. 7D BT) after a single dose of BEV. As proposed by Dr.
Waxman [91], overall anti-tumor activity is not solely determined by tumor cells’
exposure to cytotoxic drugs. Rather, it is determined by the net balance between the
angiogenesis inhibition-induced tumor cell starvation and the tumor cytotoxicity due to
the exposure to cytotoxic drugs. Additionally, cytotoxic drugs may enhance the activity
of anti-angiogenic agents and increase the sensitivity of blood vessels to VEGF
inhibition, thereby augmenting antitumor activity in the combination setting [201], even
with decreased cytotoxic drugs exposure in the tumor. Thus the increased antitumor
activity for the combination therapy might derive from the above two reasons.
45

Furthermore, although the volume of distribution in tumor compartment is not identical
to tumor volume, it may serve as an early indicator of the therapeutic response. In our PK
study, we used population modeling and covariate analysis to assess the effect of BEV on
the volume of distribution of TPT in tumor compartment at the day of TPT
administration. The results indicated that the use of BEV significantly decreased the
volume of distribution in tumor compartment, which was confirmed by the tumor
efficacy study in a different cohort of mice─a significant tumor volume reduction was
observed when compared the combination therapy to monotherapy after two weeks of the
initial treatment. Last, the combination therapy with a single dose of BEV and TPT did
enhance the tumor response; however, the combination therapy with multiple doses of
BEV and TPT did not benefit antitumor activity. TPT alone had the least antitumor
activity, while multiple BEV only had similar antitumor activity when combing TPT.
This result clearly indicated that multiple doses of BEV dominated the tumor response
and the antitumor activity caused by a single dose of TPT was diminished.
In summary, in the present study we observed significant changes in TPT
disposition after a single BEV dose in our orthotopic RMS model. In brief, a single dose
of BEV had significant effect on the systemic elimination and clearance of TPT, and
time-dependently regulated TPT elimination from tumor compartment. Though a
substantial antitumor activity after a single dose of BEV and TPT combination was
detected, BEV did not alter TPT penetration or exposure into tumor tissue. Furthermore,
TPT penetration and efficacy were not affected after multiple doses of BEV
administration. Although using drug penetration and antitumor activity as the end points
of the study, we were unable to identify the optimal schedule of the combination therapy.
However, our results provide crucial insights into the effect of coadministration of BEV
on TPT PK changes. The overall effects of anti-angiogenic agents on tumor vasculature
and microenvironment, resulting in the net balance of the antiangiogenesis-mediated
pharmacologic actions may be the determinants for the cytotoxic drug penetration.
Cytotoxic drugs may reversely sensitize the antitumor activity of the anti-angiogenic
agents. This study highlights the complexity of PKPD interaction that may take place
when antiangiogenic agents and cytotoxic drugs are combined and cautions that careful
consideration and more mechanistic investigation should be made before the usage of the
combination of anti-angiogenic agents with cytotoxic drugs for cancer treatment.
46

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58

VITA
Zaifang Huang was born in 1980 in P. R. China. She received her bachelor degree
in Pharmacy and Master of Science in pharmaceutical science from Zhejiang University.
She entered the Pharmaceutical Sciences Graduate Program with a major in
pharmaceutics at the College of Pharmacy, University of Tennessee Health Science
Center in August 2009. She was accepted into the lab of Dr. Clinton F. Stewart in
Department of Pharmaceutical Science in St. Jude Children's Research Hospital. She
expects to graduate in December 2011 with the degree of Master of Science in
Pharmaceutical Sciences.
59